مشاهده‌ مشخصات مقاله

A Technique Based on Chaos for Brain Computer Interfacing

Authors	A. Banitalebi S. K. Setarehdan G. A. Hossein-Zadeh
Conference	چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران
Abstract	A user of Brain Computer Interface (BCI) system must be able to control external computer devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. There are problems associated with classification of different BCI tasks. In this paper we propose the use of chaotic indices of the BCI. We use largest Lyapunov exponent, mutual information, correlation dimension and minimum embedding dimension as the features for the classification of EEG signals which have been released by BCI Competition IV. A multi-layer Perceptron classifier and a KMSVM( support vector machine classifier based on kmeans clustering) is used for classification process, which lead us to an accuracy of 95.5%, for discrimination between two motor imagery tasks.
قیمت	برای اعضای سایت : 100,000 Rial برای دانشجویان عضو انجمن : 20,000 Rial برای اعضای عادی انجمن : 40,000 Rial

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